Ambiguity, value of information and forest rotation decision under storm risk

Patrice Loisel, Marielle Brunette () and Stéphane Couture

Working Papers of BETA from Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg

Abstract: Storm is a major risk in forestry. However, due to the more or less pessimistic scenarios of future climate change, storm frequency is now ambiguous and only partially known (i.e., scenario ambiguity). Furthermore, within each scenario, the quantification of storm frequency is also ambiguous due to the differences in risk quantification by experts, creating a second level of ambiguity (i.e., frequency ambiguity). In such an ambiguous context, knowledge of the future climate through accurate information about this risk is fundamental and can be of significant value. In this paper, we question how ambiguity and ambiguity aversion affect forest management, in particular, optimal cutting age. Using a classical Faustmann framework of forest rotation decisions, we compare three different situations: risk, scenario ambiguity and frequency ambiguity. We show that risk and risk aversion significantly reduce the optimal cutting age. We also show that both scenario and frequency ambiguities reinforce the effect of risk. Inversely, ambiguity aversion has no effect. The value of information that resolves scenario ambiguity is high, whereas it is null for frequency ambiguity.

Keywords: Rotation decision; Risk; Ambiguity; Ambiguity Aversion; Risk Aversion; Value of Information; Forests; Faustmann criterion. (search for similar items in EconPapers)
JEL-codes: D81 D90 Q23 (search for similar items in EconPapers)
Date: 2022
New Economics Papers: this item is included in nep-env and nep-upt
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Related works:
Working Paper: Ambiguity, value of information and forest rotation decision under storm risk (2023)
Working Paper: Ambiguity, value of information and forest rotation decision under storm risk (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:ulp:sbbeta:2022-26

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